DXF Export Java is a Java library for exporting CAD entities, along with their properties, to stream or AutoCAD DXF files at high speed and with ease. Creating a new DXF file takes only one call of the exporter class, provided that user data has been prepared and loaded to the required fields beforehand. The library handles all major entities, including Arc, Bezier, Circle, Ellipse, Hatch Pattern, Line, Multi-line Text, Pixel, Polyline, Rectangle, and Text. It also supports layers, colors, line styles, and other important properties. Source code and working demos are included.
DeltaQt is a cross-platform library of C++ classes and functions for parsing of DELTA (DEscription Language for TAxonomy) files, and is part of the Free DELTA initiative. Support for all major data-related DELTA directives is planned. Typesetting directives are beyond the scope of the project, and support for them is not planned. Support for RTF formatting within comments, notes, descriptions, etc. is planned. All data defined by supported DELTA directives (including comments and annotations) will be parsed into memory. Qt (core) is used extensively.
EJDB is an embedded JSON database engine. It aims to be a fast MongoDB-like NoSQL library that can be embedded into C/C++/Nodejs/Python3/Lua applications. It features collection-level write locking, collection level transactions, string token matching queries, and a Node.js binding.
EpochX is a genetic programming framework. It is designed specifically for the task of analyzing evolutionary automatic programming, so is ideal for researchers who require an extendable system for studying the effects of new operators or procedures. It supports 3 popular representations - Strongly-Typed tree GP, Context-Free Grammar GP, and Grammatical Evolution.
EO is a template-based, ANSI-C++ evolutionary computation library that helps you to write your own stochastic optimization algorithms quickly. Evolutionary algorithms form a family of algorithms inspired by the theory of evolution, and solve various problems. They evolve a set of solutions to a given problem in order to produce the best results. These are stochastic algorithms because they iteratively use random processes. The vast majority of these methods are used to solve optimization problems, and may be also called "metaheuristics". They are also ranked among computational intelligence methods, a domain close to artificial intelligence. With the help of EO, you can easily design evolutionary algorithms that will find solutions to virtually all kind of hard optimization problems, from continuous to combinatorial ones.